Assistant Professor

6 days ago


Delhi, India Atria University Full time

About Us Atria University desires and enables research impact beyond publications. We operate without traditional departments (HoDs). Faculty are housed within Centers of Excellence (CoE), fostering deep, cross-disciplinary collaboration. This role will primarily be affiliated with the Bio-AI Hub/CoE. Why this role Help build India’s next wave of Bio-AI: genomic and protein foundation models, multi-omics modelling, generative design for enzymes and pathways, and AI-assisted DBTL loops with wet-lab partners. You’ll have real datasets, compute, and translational collaborations. What you’ll do Lead research on Bio-AI foundation models (e.g., DNA FMs, protein LMs, generative design/diffusion for sequences/structures). Ship artifacts: open-source code, trained weights, datasets, and benchmarking pipelines; submit to top venues; file IP where appropriate. Collaborate intensively with faculty in the wet-lab/clinical CoEs to design unified, problem-driven interdisciplinary curricula and research projects (strain/enzyme design, microbiome, diagnostics, materials for bioenergy, etc.). Teach light, high-impact: 2–3 project-based, 4-credit sprints/year; mentor student teams on real problems. Win grants & lead consortia: craft proposals, coordinate multi-partner projects, and grow the Bio-AI Hub, explicitly ensuring student research teams are integrated into grant deliverables. What will set you up for success (must-have) PhD (or ABD close to defense) in CS/AI/Computational Biology/Bioinformatics/Applied Math or related. Strong first-author record or open-source impact in sequence modelling (Transformers/GraphNNs/Diffusion) applied to genomics/proteomics. Hands-on with PyTorch, training/evaluating large models, and reproducible ML (MLOps, containers, Slurm/cloud). Exposure to workings of foundation models Nice to have Experience with at least one: genomic FMs (e.g., Enformer-style, Nucleotide/Genome LMs), protein LMs (e.g., ESM/ProtT5/MSA), or similar Enzyme/pathway design, multi-omics integration, metagenomics. Joint work with wet-lab/clinical teams; familiarity with DBTL or LIMS/ELN. Prior grant success (PI/Co-PI) or industry collaboration. What we offer Research-first load: concentrated teaching in short sprints; significant time for research. Compute & infra: access to GPUs, curated omics datasets, secure data rooms, and DevOps support. Translational runway: partnerships with industry and research organizations; pathways for IP and spinouts. Community: interdisciplinary peers in AI and Life Sciences; vibrant Bengaluru ecosystem.



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